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Site-Specific Deployment Optimization of Intelligent Reflecting Surface for Coverage Enhancement

Dongsheng Fu, Xintong Chen, Jiangbin Lyu, Liqun Fu

TL;DR

This work addresses site-specific IRS deployment for coverage enhancement in multi-building environments by explicitly modeling IRS element radiation patterns and AP antenna patterns. It develops an ILP-based framework that discretizes candidate IRS locations on building facets and optimizes UE-IRS associations to maximize average ergodic throughput, with a Lagrangian-relaxation approach to solve the resulting NP-hard problem. The results show that ERP and antenna patterns significantly affect link-level performance, and that active IRS configurations can achieve substantially better site-wide coverage and fairness than passive IRS under practical element counts. The study highlights the practical value of considering site-specific propagation and hardware patterns in IRS deployment and points to future work on multi-AP scenarios, inter-IRS reflections, and resource scheduling.

Abstract

Intelligent Reflecting Surface (IRS) is a promising technology for next generation wireless networks. Despite substantial research in IRS-aided communications, the assumed antenna and channel models are typically simplified without considering site-specific characteristics, which in turn critically affect the IRS deployment and performance in a given environment. In this paper, we first investigate the link-level performance of active or passive IRS taking into account the IRS element radiation pattern (ERP) as well as the antenna radiation pattern of the access point (AP). Then the network-level coverage performance is evaluated/optimized in site-specific multi-building scenarios, by properly deploying multiple IRSs on candidate building facets to serve a given set of users or Points of Interests (PoIs). The problem is reduced to an integer linear programming (ILP) based on given link-level metrics, which is then solved efficiently under moderate network sizes. Numerical results confirm the impact of AP antenna/IRS element pattern on the link-level performance. In addition, it is found that active IRSs, though associated with higher hardware complexity and cost, significantly improve the site-specific network coverage performance in terms of average ergodic rate and fairness among the PoIs as well as the range of serving area, compared with passive IRSs that have a much larger number of elements.

Site-Specific Deployment Optimization of Intelligent Reflecting Surface for Coverage Enhancement

TL;DR

This work addresses site-specific IRS deployment for coverage enhancement in multi-building environments by explicitly modeling IRS element radiation patterns and AP antenna patterns. It develops an ILP-based framework that discretizes candidate IRS locations on building facets and optimizes UE-IRS associations to maximize average ergodic throughput, with a Lagrangian-relaxation approach to solve the resulting NP-hard problem. The results show that ERP and antenna patterns significantly affect link-level performance, and that active IRS configurations can achieve substantially better site-wide coverage and fairness than passive IRS under practical element counts. The study highlights the practical value of considering site-specific propagation and hardware patterns in IRS deployment and points to future work on multi-AP scenarios, inter-IRS reflections, and resource scheduling.

Abstract

Intelligent Reflecting Surface (IRS) is a promising technology for next generation wireless networks. Despite substantial research in IRS-aided communications, the assumed antenna and channel models are typically simplified without considering site-specific characteristics, which in turn critically affect the IRS deployment and performance in a given environment. In this paper, we first investigate the link-level performance of active or passive IRS taking into account the IRS element radiation pattern (ERP) as well as the antenna radiation pattern of the access point (AP). Then the network-level coverage performance is evaluated/optimized in site-specific multi-building scenarios, by properly deploying multiple IRSs on candidate building facets to serve a given set of users or Points of Interests (PoIs). The problem is reduced to an integer linear programming (ILP) based on given link-level metrics, which is then solved efficiently under moderate network sizes. Numerical results confirm the impact of AP antenna/IRS element pattern on the link-level performance. In addition, it is found that active IRSs, though associated with higher hardware complexity and cost, significantly improve the site-specific network coverage performance in terms of average ergodic rate and fairness among the PoIs as well as the range of serving area, compared with passive IRSs that have a much larger number of elements.
Paper Structure (20 sections, 29 equations, 7 figures)

This paper contains 20 sections, 29 equations, 7 figures.

Table of Contents

  1. Introduction
  2. System Model
  3. Positions of AP, IRSs, UEs, and Buildings
  4. AP Antenna Pattern and IRS ERP
  5. AP antenna patternlyu2019network
  6. IRS ERP
  7. Site-Specific Channel Model and Impact of Radiation Pattern
  8. AP-IRS Channel
  9. IRS-UE Channel
  10. AP-IRS-UE Channel
  11. AP-UE Channel
  12. Site-Specific LoS/NLoS Channel Model
  13. Received Power and SNR
  14. Ergodic Throughput and Coverage Indicator
  15. Problem Formulation and Optimization
  16. ...and 5 more sections

Figures (7)

  • Figure 1: Site-specific deployment of IRSs for coverage enhancement.
  • Figure 2: Single IRS deployment link performance experiments.
  • Figure 3: Ergodic throughput of the UE aided by IRS or AP-only.
  • Figure 4: Site-specific deployment of IRS to enhance coverage, considering the grids as candidate deployment locations, 100 UEs and 149 candidate deployment locations.
  • Figure 5: IRS deployment given total number of elements $N=1024$.
  • ...and 2 more figures